Corticomotor functional indices of traumatic musculoskeletal injury

Introduction: Warfighters undertake prolonged and strenuous physical tasks in hot environments, which can degrade performance and increase the risk of exertional heat injury (EHI) including heat stroke. Although various risk mitigation strategies and guidelines have been implemented, EHI continues to challenge the health and safety of warfighters1. Physiological biomarkers: Real-time non-invasive physiological monitoring is considered an effective strategy to assess heat strain and detect impending EHI2. Core temperature (Tc) is considered a key biomarker of heat strain but accurately measuring Tc in the field is difficult. Alternative methods of measuring heat strain have been proposed. Researchers have developed various prediction models to estimate Tc using one or more non-invasive physiological measures (e.g., heart rate, skin temperature)2. A Tc prediction algorithm based on heartrate has been used with the Physiological Strain Index for real-time monitoring of heat strain during military training2. Techniques and devices based on heat flow at the skin surface may also provide estimates of Tc2. Kinematic biomarkers: Gait characteristics have also been identified as potential markers of heat strain, since an increase in gait instability may indicate central nervous dysfunction3,4. An increase in crossover steps (i.e., feet overlapping) was associated with exertional heat strain3, while increased asymmetry in stride patterns between the two feet, assessed through accelerometry, was used to identify EHI personnel during military training4. Conclusion and future research: Monitoring these physiological and kinematic variables may potentially help mitigate EHI risks and maximise safety and performance of warfighters, with recent advancements in wearable technologies facilitating the ease of obtaining such data in the field. However, more robust and thorough validation of the Tc prediction algorithms by independent laboratories is required, especially during field settings and across more diverse populations (e.g., older adults, females). The accuracy (i.e., false-positive and false-negative rates) of these algorithms in identifying potential EHI cases in the field also needs to be established and the accuracy criteria may be dependent on each unit’s risk tolerance. Lastly, the traditional assumption that Tc as a definitive marker of EHI has been questioned2. Given that heat stress perturbs many physiological systems (e.g., immune, hormonal), future work in this area should consider elucidating the role of heat-induced derangements in these physiological systems in the etiology of EHI. References 1Alele FO, Malau-Aduli BS, Malau-Aduli AEO, et al. Epidemiology of exertional heat illness in the military: a systematic review of observational studies. Int J Environ Res Public Health 2020; 17(19):7037. https://doi.org/10.3390/ijerph17197037 2Buller MJ, Welles AP, Friedl KE. Wearable physiological monitoring for human thermal-work strain optimization. J Appl Physiol 2018; 124(2):432-441. https://doi.org/10.1152/japplphysiol.00353.2017 3Tay CS, Lee JKW, Teo YS, et al. Using gait parameters to detect fatigue and responses to ice slurry during prolonged load carriage. Gait & Posture 2016; 43:17-23. https://doi.org/10.1016/j.gaitpost.2015.10.010 4Buller MJ, Delves SK, Fogarty AL, et al. On the real-time prevention and monitoring of exertional heat illness in military personnel. J Sci Med Sport 2021. https://doi.org/10.1016/j.jsams.2021.04.008